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Understanding proofs of AI learning

Authors:

(1) Jongmin Lee, Department of Mathematical Sciences, Seoul National University;

(2) Ernest K. Ryu, Department of Mathematical Sciences, Seoul National University and Interdisciplinary Program in Artificial Intelligence, Seoul National University.

One summary and introduction

1.1 Notes and introductions

1.2 Previous works

2 Repeat the vertical value

2.1 Accelerating rate of the Bellman consistency operator

2.2 The accelerating rate of Bellman’s ideal opera

3 Convergence when y=1

4 Minimum complexity

5 Repeat the approximate vertical value

6 Gauss-Seidel iteration of the established value

7 Conclusion, acknowledgments, funding disclosure, and references

A preliminary

B- Evidence omitted in Section 2

C- Evidence omitted in Section 3

D- Evidence omitted in Section 4

E – Evidence omitted in Section 5

F- Evidence omitted in Section 6

Wider impacts

h restrictions

F- Evidence omitted in Section 6

Next, we prove following the main lemma

Proof of Lemma 21. First, we prove the first inequality in Lemma 21 by induction.

If k = 0,

By induction,

First, we prove the second inequality in Lemma 21 by induction.

If k = 0,

By induction.

Now we prove the first rate in Theorem 7.

For the second rates of Theorem 7, we present the following lemma.

Now we prove the second rate in the seventh theorem.

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